1. Field of the Invention
The present invention relates to a self-diagnosis and self-repair system, and more particularly, to a system capable of making self-diagnosis of the degraded state, the operating state and the like of an apparatus by utilizing artificial intelligence and knowledge engineering which have been studied extensively in recent years as well as adopting fuzzy inference and making self-repair as required.
2. Description of the Prior Art
In the development of precision instruments, industrial machines and the like, expert systems utilizing artificial intelligence (so-called AI) techniques have been being studied extensively in recent years for the purpose of realizing labor saving in maintenance work and long-term automatic operation. The expert systems include one for making self-diagnose to judge whether or not a fault is caused in an apparatus and making self-repair of the fault caused.
In a fault diagnosis system by the conventional expert system, such limitations have been pointed out that, for example, (A) there is no versatility in knowledge, which makes it impossible to make fault diagnosis on a variety of objects, (B) diagnosis cannot be made on unknown faults, (C) the quantity of knowledge required for fault diagnosis is increased explosively as an object becomes complicated, thus making implementation difficult, and (D) it is difficult to acquire knowledge.
More specifically, in a conventional automatic control system and fault diagnosis system, an actuator corresponding to a sensor is basically made to operate on the basis of an output of the sensor. That is, one type of automatic control and fault diagnosis has been made by a predetermined combination of a sensor and an actuator. Accordingly, a certain sensor basically corresponds to a particular actuator, and the relationship therebetween has been stationary. Therefore, the conventional system has the following disadvantages: (a) The relationship between parameters of the sensor and parameters of the actuator must be clearly expressed numerically. (b) From the reason mentioned in the above item (a), the relationship between parameters of the sensor and parameters of the actuator depends largely on an object. Accordingly, the conventional system is lacking in versatility, that is, cannot be utilized for a variety of objects. (c) The relationships between parameters of respective sensors and between parameters of respective actuators have no relation with control. Accordingly, only simple control based on the relationship between the parameters of the sensors and the parameters of the actuators which correspond to each other can be carried out, and faults which can be coped with are previously restricted and unknown faults cannot be handled. (d) From the reason mentioned in the above item (3), secondary effects exerted on parameters of other actuators which might be caused by the operation of parameters of an arbitrary actuator cannot be forecast.
In the conventional automatic control system and fault diagnosis system, therefore, only fault diagnosis based on sets respectively including independent sensors and actuators and fault repair based on the fault diagnosis have been made in such a manner that forecasting fault A is made on the basis of a set A of a sensor A and an actuator A, forecasting fault B is made on the basis of a set B of a sensor B and an actuator B, and forecasting fault C is made on the basis of a set C of a sensor C and an actuator C.
The applicant of the present application and the like have proposed as a technique associated with the present invention a new system for making self-diagnosis and/or self-repair by adopting an image forming apparatus as an objective machine so as to eliminate the disadvantages of the prior art (see U.S. patent application Ser. Nos. 07/588,191 and 07/588,177).
Qualitative inference used in the above described self-diagnosis and/or self-repair system already proposed is complete as the approach of determining the qualitative transition from a group of equations and the initial state. On the other hand, the qualitative inference has such an inevitable destiny that an ambiguous expression is not admitted as the state representation of an objective system (machine) because inference in the form of a qualitative, that is, symbolic expression is drawn. The qualitative inference is insufficient as the approach of making fault diagnosis and repair by handling information such as "ambiguous information" often seen in the maintenance activity, for example, information "this may be normal or abnormal" as the state of the machine.
Furthermore, when the fault diagnosis utilizing degradation and fault hysteresis information on respective components constituting the machine is synthesized, a fault diagnosis system and/or fault repair system having a higher degree of completion cannot be constructed unless an inference method having logic using any other method of representation added to the qualitative inference already proposed, and the approach of handling ambiguous information added thereto is considered.
The inventors of the present application have invented a self-diagnosis and self-repair system having a higher degree of completion by combining the fuzzy theory which is a theory mathematically handling ambiguity with the qualitative inference used in the above described self-diagnosis and/or self-repair system already proposed.